Genetec Adds Machine Learning-Based License Plate Recognition to AutoVu
Genetec says its AutoVu machine learning core reduces common ALPR misreads and false positives compared to traditional rule-based ALPR technology.
The Genetec AutoVu SharpV camera.
MONTRÉAL— Genetec unveils AutoVu MLC (AutoVu machine learning core), a new machine learning-based engine for Security Center AutoVu, its automatic license plate recognition (ALPR) system.
AutoVu MLC replaces traditional rule-based ALPR technology with machine learning-based algorithms to reduce common ALPR misreads and false positives, according to the company.
With AutoVu MLC, Genetec says customers in law enforcement, parking, and critical infrastructure will be able to reduce the incidence of false-positive reads to a fraction of a percent (measured at up to 70% reduction from traditional algorithm performance).
These performance gains also extend to include advanced vehicle analytics, such as state origin identification.
“Not only does AutoVu MLC further reduce misreads, it improves vehicle analytics, such as plate State recognition, providing additional insights and data for the operator. Officers benefit from higher reliability when identifying a vehicle of interest — empowering them to act decisively, based on credible information,” says Robert Amante, Security Center AutoVu product manager at Genetec.
The AutoVu MLC is available now as a firmware update for new and existing AutoVu SharpV hardware from Genetec-certified channel partners and integrators.
It does not require hardware upgrades and can run on AutoVu SharpV and most SharpX cameras already deployed in the field. AutoVu MLC is expected to be available for AutoVu SharpX ALPR cameras in Fall 2018.
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